Benchmark Python Snippets Online

Perfpy allows you to benchmark python snippets online and share them with other people. You can measure the performance and memory usage of code on different python versions in this sandbox environment.

The tool can compare and test the speed of 3rd-party libraries or library versions, so you can find out which is the fastest or consumes less memory between numpy, opencv, scipy and pandas for a certain function.

Packages

List packages as it's done in a requirements.txt file. Learn more

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numpy
 
 
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Setup

Runs before the benchmark, and it is not measured. Good place to import libraries and prepare data. Learn more

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import numpy as np
def bit_length1(arr):
    # assert arr.max() < (1<<53)
    return np.ceil(np.log2(arr)).astype(int)
    
def bit_length2(arr):
    # assert arr.max() < (1<<53)
    return np.frexp(arr)[1]
 
 
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Code 1

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for __ in range(10):
    bit_length1(data)
 
 
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Code 2

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for __ in range(10):
    bit_length2(data)
 
 
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Code 3

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for __ in range(10):
    bit_length3(data)
 
 
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Teardown

Results

Fastest

Code 2

5.87 ms

170 op/s

Speed

Benchmark	Runtime	Operations	VS	Visual
Code 2	5.87 ms	170 op/s	1×	0.005871319056799014
Code 3	31.2 ms	32.0 op/s	5×	0.03121881280094385
Code 1	36.0 ms	27.7 op/s	6×	0.036041573931773506

Memory

Benchmark	Peak Memory	Score	VS	Visual
Code 2	1.32 MB	7.11	1×	1316
Code 1	1.57 MB	6.25	1.19×	1572
Code 3	3.27 MB	5.99	2.5×	3272

Output

Code 1

<string>:8: RuntimeWarning: divide by zero encountered in log2
<string>:8: RuntimeWarning: invalid value encountered in cast

Code 2

No output

Code 3

No output